Interview with professor Sae-Young Chung

The EE Newsletter conducted interviews with people in laboratories belonging to the department of electrical engineering to provide various information about laboratories for students within the department. In this EE Newsletter, an interview was conducted with Professor Sae-Young Chung about the ITML Lab (Information Theory and Machine Learning Laboratory). In the ITML Lab, research based on deep-learning and AI (Artificial Intelligence) are underway.


1. Introduction of Professor Chung and his laboratory

I was awarded a Ph.D. degree from MIT in 2000, worked in a communication company for four years, and then came to KAIST (Korea Academic Institute of Science and Technology) in January of 2005. At first, I was usually studying information theory and wireless communication. Recently, however, I have been focused on research about deep-learning and AI, based upon research in information theory.


2. Explanation of the research field

Information theory is about studying limitations of inherent performance through various conditions. For example, one may attempt to find the maximum transmittable information quantity and study how to design a system to have a satisfying performance. Until Shannon created the field of information theory, research for information was not systematic, but after Shannon appropriate studies became possible by using the concepts which quantify information, such as entropy and mutual information. For this reason, information theory is a basic philosophy and is applicable to other fields. Indeed, researchers who studied it do active work in economic engineering, bioinformatics, and so on. These days, research on information theory is very active because research on deep-learning is active.

Deep-learning is too complex to study theoretically. However, deep-learning is what we consider “learning”, as it exemplifies the procedure during which a signal is transmitted and processed in neural networks. If the “how” regarding important information being included in a signal is analyzed, it will help researchers better understand deep-learning. Currently, though brain science has been greatly developed, brains are still only partially understood. Deep-learning has a similar aspect. Most of the inventors of AlphaGo, deep-mind engineers, are not professional in Go. Even though they were helped by Go-specific experts, not top players like Se-Dol Lee, AlphaGo developed so much that it defeated Ke Jie 3-0, implying that there is no one who can compete with it. The engineers can clearly explain the algorithm for training AlphaGo, but cannot explain why it conducts such moves during specific game situations. To explain that, they should analyze the millions of existing parameters, and this is impossible. Therefore, even though those engineers couldn’t understand Go perfectly, it is really interesting that they can create a Go AI which surpassed human abilities only with basic principles of machine learning. Similarly, in the future, acceleration of this research will trigger the advent of forms of AI which exhibit brilliant performances in other fields.

As in many other fields, it is important for deep-learning to strike a balance between basic theory and trial-and-error. Therefore, basic theories like information theory play crucial roles. At the same time, trial-and-error leads researchers to learn many things and performance becomes enhanced. An appropriate harmony between basic theory and trial-and-error methodology will result in the development of deep-learning.


3. Detailed research which is underway in the laboratory

Among the three fields of machine learning, which are Supervised Learning, Unsupervised Learning, and Reinforcement Learning, our laboratory focus on Reinforcement Learning. Specifically, we study Deep-Reinforcement Learning, where deep-learning is applied.

Reinforcement Learning involves choosing a behavior with a maximum reward. This is similar to the process through which students study problems they got wrong to increase their test score. If Reinforcement Learning is used in AI significantly, much more complex and delicate work can be accomplished. However, more research must be carried out. As with incidents like the accident in which an autonomous vehicle from Tesla crashed into a white truck after mistaking the truck for the sky, AI frequently makes some mistakes which people do not. Human beings possess common sense, which is an attribute they have learned over a long period of time, but it is hard to teach common sense to an AI. Moreover, considering that human beings complete various general tasks, but AI can do only specific work, AI is still at an elementary level.

We study Deep Reinforcement Learning by using an arcade game and various conditions which are artificially constructed. It is hard to apply theory to an autonomous vehicle but, in the case of application in the game, a new algorithm can be evaluated more quickly. Therefore, using the game is more efficient to find a good algorithm. We also conduct research on radar applied to deep-learning. The idea comes from bats, who receive echolocation signals and use their neural networks to distinguish food from obstacles. For example, the method of compressed sensing in the field of information theory, which is adapted for deep-learning, was applied to radar, and this yielded enhanced performance. In addition, we study IoT (Internet of Things) where machine learning is applied. For instance, even though people do not directly turn on a heating system or an air conditioner, the system detects their intention for both comfort and energy-efficiency.


4. Prospects of the research area

Now is the era of information. Among the ten companies with the top market capitalization, seven companies are of IT and they are all investing in AI with great expectations. In this regard, the future of AI seems to be bright. However, no one is sure what AI will become. “AI winter”, which is a term for a period of reduced funding and interest in artificial intelligence research, has happened several times because, in the past, computing power was not enough to support AI. In other words, when a new algorithm for AI is proposed, AI became popular for a short time and then was again ignored. On the contrary, the fields of computer, internet, and mobile communication have been developed constantly for over 20 years. I think this is the time to begin and expect constant development from AI research.


5. The scope of the laboratory, atmosphere, and career after graduation

There are nine total students, comprised of four master students and five doctoral students. We have a seminar and lunch once per week and we go skiing together in winter.

After graduation with a doctorate, one becomes a professor or a researcher in a laboratory. Last year, Dr. Lee, who graduated from our laboratory with a Ph.D. became the first female professor in the department of electrical engineering at POSTECH. Masters students may enter large companies or laboratories like ETRI. One recent graduate entered a venture company concerned with deep-learning and machine learning.


6. Is there any subject you recommend to students wanting to enter your laboratory? Or what attitude students should have to accomplish that?

I want students who are interested in deep-learning, AI, and basic studies such as information theory and mathematics. When I was an undergraduate, I attended some classes in the departments of physics and mathematics, and it really helped me when I was researching. It is really important to look at the big picture of fundamental questions and to think deeply. In mathematics, lectures about probability, one of the fundamental fields, are especially important.


7. Do you have any advice for our EE Newsletter readers?

The trend of deep-learning research is rapidly changing. For example, only one year after the emergence of AlphaGo, AlphaGo Zero was created. Because of the quick trend changes, the basics are really important. With strong basics, one can swiftly adapt to a new research field. With weak basics, if someone conducts a study which is active now, it is hard for him to change his research field.

Just as concentrating on one important page to make it yours yields longer-lasting knowledge and more scholarly delight than reading a whole book, ask fundamental questions and study from the basics.


Thank you, professor Sae-Young Chung, for your generous agreement to this interview.

Reporter Minki Kang

Reporter Yoonseong Kim


Prof. HyunChul Shim

Q. Hello, Could you introduce yourself?

A. Hello, My name is HyunChul Shim. I joined the CNS group in the School of Electrical Engineering from the School of Mechanical and Aerospace Engineering in June. I went to the Department of Mechanical Design at Seoul National University. I was interested in the field of control engineering that the machine was controlled automatically. The first unmanned aerial vehicle contest in the United States was the occasion to decide my major as the control of the helicopter.


Q. Why do you move to the School of Electrical Engineering from the School of Mechanical and Aerospace Engineering this semester?

A. After a few years of research in the School of Mechanical and Aerospace Engineering, I began to think about my research identity. Because my research is so convergent, I feel the need to expand my research area. Since the School of Mechanical and Aerospace Engineering is limited to the aviation sector, I was attracted to the School of Electrical Engineering, which is the largest research field. 


Q. Could you explain about your research area?

A. I am doing research in various fields such as mechanical engineering, electronics engineering, and aeronautical engineering rather than just one field. The area of greatest interest is the unmanned autonomous mobile system in which a system moves by itself. There are researches about it, such as unmanned aerial vehicles, autonomous vehicles, and robots. These three studies are also combined together, including a flying robot that combines an unmanned aircraft and a robot, a flying car that combines an unmanned aircraft and an automobile, and an autonomous mobile robot that combines an autonomous vehicle and a robot. And we are also developing an autonomous flying car that can be combined with all three. Our lab is a lot of work, so our research might seem a little tough when people are sitting and doing a simulation. But it’s a great lab for those who want to do more active research. And because the results are visible to the eye, companies are also interested in our laboratory.


Q. What kind of lab do you want to make in the future?

A. I would like to do such research that has a vision and a thrill. Actually, I do. We look ahead to the future. I think that insight is important to look promising first. Most researchers are not aware of unmanned aircraft in 1991 when I first started an unmanned airplane, but I was just starting to have fun. Also, I started to study autonomous driving in 2009 when researchers did not have much interest in Korea yet. As an aviation professor, I thought that it would be possible to take part in the development of a promising Mars exploration robot that would deal with autonomous navigation. Since I have been in various fields so far, my goal is to create innovation through convergence research. This time, NASA JPL invited us to come up with a suggestion to launch a helicopter on Mars. Our lab is very well received at home and abroad, and we also have suggestions for research. I am making a lot of effort to take advantage of these opportunities.


Q. Which qualification do you request to students? 

A. First of all, the control system is the most important subject and you need to learn circuit design, C language, Python coding, artificial intelligence, and robotics. Our labs have many research areas, so anyone who feels joyful about touching and making various things will fit in our lab. We also welcome students who are active, active, and motivated because they have a lot of physical activity.


Q. Finally, do you have something to tell students?

A. I want students to have a bigger and broader view. Although there are many things that can be done only by electronics engineering in the future, students should build a foundation for basic mathematics, physics, and informatics, and do not have a bias against various fields. And I would like students to be passionate about throwing away the passive figure. Korea is not much different from the stage of copying what advanced countries did in the 8th and 90s, but now China is adding more creativity to it. China has been our late player in the past, and now it is overtaking us in many areas. I am hoping that students will be more active and competent because we have only a small amount of technology in Korea. When you look at a rabbit and a turtle, the rabbit loses to the turtle because he sleeps, but there are many rabbits in the world who do not sleep. It is difficult to win the geniuses who study without sleep. When we look at those geniuses who try so hard, I think our students should really jump in and study and study.


Reporter Minjun Cha  /

Professor Hyunju Lee

As undergraduate students, you must now be dreaming of your aspirations and taking the very first step towards your dream – I can confidently say that this is one of the most important and happiest moments of your life. For a moment, let’s forget about all your much too down-to-earth worries and concerns, such as your abilities, your current situations, balancing between work and parenting, and so forth. Instead, let’s think about what you truly would love to do if you were given everything you think you lack.

“Adding dates to your dream, it becomes a goal.
Dividing it by timeline, it becomes a plan.
Then by simply following your plans,
In the end, your dream will be realized.

Dream + Date = Goal
Goal / Time = Plan
Plan * Plan = Realization of Dream”
-Excerpt from the dream note of a professional golfer, Hyojoo Kim-

The above is an excerpt from the dream note of Hyojoo Kim, a professional golfer. Every female EE students at KAIST are of excellent qualities and diligence, and has the potential to realize their goals. Therefore, setting the right goal for yourself will be very important.


Professor Hyunmin Bae

Nowadays, the electrical engineering market is in a bad shape. There are over 600 semiconductor companies in China alone, and many start to worry whether they should leave and find another field of specialization. In the olden days, one could become a king with the control of iron. However, during Chosun-Dynasty, handling iron was no longer a talent and became a mundane task for blacksmiths. Through this example, we can realize that the scarcity of work, not its type, was the main value criterion. 

James Watt developed steam engine using iron and pioneered the Industrial Revolution. Developing a new concept using the conventional technologies can produce high values. No man-made technologies have as high accuracy and low form factor as electrical engineering. Therefore, electrical engineering can become a very useful tool to realize something much bigger. I wish that KAIST EE students would acquire knowledge of various areas and use their specialty, electrical engineering, to develop new concepts and devices.

Professor Minkyu Je

Through a series of comparisons between the graduates of well-renowned universities abroad and KAIST, I came to realize that KAIST graduates are of superb talents. Especially in the field of electrical engineering, both the research potential and achievements are highly praised all around the world. Therefore, you should always be proud of being KAISTians. Of course, we should never forget that these great reputations came from our alumni and that we have to live up to the name of KAIST.

Nowadays, it is becoming more and more important to have collaborations with others. You should not only focus on your studies and research, but also on your personal relationship with others. While the word ‘technological convergence’ is prevalent, you should first have a deep understanding of your own field of specialization before you can consider convergence. To achieve this, you should also have ability and adaptability to newer technologies.

Professor Minkyu Je

Frankly speaking, when I was a student, I never thought I wanted to become a professor. I believe that one’s goal should be what research one wishes to delve into, and not the professorship itself. Regardless of the location in which you obtain your degrees, once you focus and enjoy your research, great opportunities will come.

I strongly believe that KAIST students have the potential to become whoever they wish to be, if only they would focus on their research.

Professor Hoi-Jun Yoo

Technology should be centered on people. While technology has been developed based on the natural sciences, it needs to be more human-centered. We need the convergence of the humanities, business administration, as well as various fields of engineering such as bio-medical engineering. KAIST EE should be the pioneer in developing the core personnel for such development.

Sunhyung Kwon (EE graduate)

Dear fellow EE students! You are the future leaders of the IT industry of Korea ! If you conduct your research with pride and sense of duty, I believe that you will be able to bring happiness to the mankind, which accordingly will bring happiness to you as well.

Yoon Ki Huh (EE graduate)

I personally wish that graduates of KAIST would join such companies as POSCO and show their outstanding abilities. KAIST has a great environment for juggling academic work and research. During undergraduate courses, try to absorb the fundamental theories and when you proceed to graduate course, do apply the learned theories for actual implementation. I suggest that you keep on carrying out the ‘Education -> Training -> Implementation -> Analysis & Redesign -> Strategy’ processes.

Professor Sukhee Lee

While I got a number of offers from various companies and universities, I had no intention of joining a company in Korea. Instead, I chose KAIST for its excellent research environment, as well as great students, and I wanted to contribute to the development of technology in Korea.